Temporal variability of sea surface temperature affects marine macrophytes range retractions as well as gradual warming

Record mean sea surface temperatures (SST) during the past decades and marine heatwaves have been identified as responsible for severe impacts on marine ecosystems, but the role of changes in the patterns of temporal variability under global warming has been much less studied. We compare descriptors of two time series of SST, encompassing extirpations (i.e. local extinctions) of six cold-temperate macroalgae species at their trailing range edge. We decompose the effects of gradual warming, extreme events and intrinsic variability (e.g. seasonality). We also relate the main factors determining macroalgae range shifts with their life cycles characteristics and thermal tolerance. We found extirpations of macroalgae were related to stretches of coast where autumn SST underwent warming, increased temperature seasonality, and decreased skewness over time. Regardless of the species, the persisting populations shared a common environmental domain, which was clearly differentiated from those experiencing local extinction. However, macroalgae species responded to temperature components in different ways, showing dissimilar resilience. Consideration of multiple thermal manifestations of climate change is needed to better understand local extinctions of habitat-forming species. Our study provides a framework for the incorporation of unused measures of environmental variability while analyzing the distributions of coastal species.


Figure S1
Independent contribution (I value) in the hierarchical partitioning analysis of variables discriminating between persistence and extirpation populations for each macroalgae species.Dendrogram at top shows clustering of species whose extirpation/persistence patterns can be explained by the same factors.See Table S1 in Supporting information for a description of the variables.SST: sea surface temperature.

Figure S2
Non-metric multidimensional scaling (NMDS) ordination of the sites where extirpation or persistence has occurred over the baseline and resurvey periods in the Northern Spanish coast.The change in autumn mean sea surface temperature, seasonality and skewness showed a gradient direction able to explain the extirpation-persistence distribution (e.g.extirpated populations tend to increase when the seasonality anomaly increases over time).Longer arrows show stronger associations (r 2 ).Macroalgae populations studied are Fucus serratus, F. vesiculosus, Himanthalia elongata, Laminaria hyperborea, L. ochroleuca and Saccorhiza polyschides.See Supporting information for a description of the variables (Table S1), and the NMDS scores (Table S2).SST: sea surface temperature.

Figure S4
Performance of the consecutive disparity index (D; Fernández-Martínez et al 2018), a measure of temporal variability.Here we provide a comparison of a real sequence of sea surface temperature (SST) and a randomly generated time series with similar longitude, minimum and maximum values.
The real data (in red) is a one-year time sample sequence SST from Burela (Galicia), where local extirpation of Himanthalia elongata occurred.D is higher in the random series due to its lack of autocorrelation between consecutive data (greater fluctuations) in comparison with the real SST time series.

Figure S5
Anomalies in the frequency of days above the specific thermal threshold of each macroalgae species at extirpated and persistent populations (black and red dots respectively).Anomalies were calculated as the difference between the resurvey period  and the baseline period (1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990).The anomalies for Fucus vesiculosus are not shown since its thermal threshold was above the maximum SST registered in the time series.Locally extinct (extirpated) and persistent populations of six macroalgae species were studied (Fucus serratus, F. vesiculosus, Himanthalia elongata, Laminaria hyperborea, L. ochroleuca and Saccorhiza polyschides).SST: sea surface temperature.

Table S2
Correlations (r 2 and p-values) and scores of environmental variables in the non-metric multidimensional scaling (NMDS).In bold are shown the variables obtaining also an independent contribution (I value) above 0.5 in the hierarchical partitioning analysis (see Fig.2in main text and Fig.S1in Supporting information).
for all variables.